bdynsys (version 1.0)

PhasePortraitModelTrajectories: Phase Potrait with Modeled Trajectories for Specified Entities

Description

phaseportmod creates a phase portrait (velocity plot, vectorfield) based on the two differential equations that were considered to be the overall best models for indicator 1 and indicator 2. The user may specify entities for which he/she wants to obtain the predicted (modeled) trajectories over the phase portrait. The user may extend the period of time for the modeling to get future-predicted trjectories of the entities based on the models. It calls the function preprocess_data. It requires the packages plm, pracma, deSolve and graphics.

Usage

phaseportmod(dataset, yearnr, xv, yv, rangeX, rangeY, param, f, entidx1, 
entidx2, entidx3, entidx4, entidx5, entidx6)

Arguments

dataset

a plm, apdata.frame panel data frame.

yearnr

number of years for which the user wants to produce the phase portrait and obtain the modeled trajectories of the specified entities.

xv

a reference to variable from the paneldata to be included as indicator 1 in the modeling procedure.

yv

a reference to variable from the paneldata to be included as indicator 2 in the modeling procedure.

rangeX

defines the range of the indicator 1.

rangeY

defines the range of the indicator 2.

param

a vector with parameters from the two models in f.

f

a function that contains the models of the two indicators.

entidx1

index of an entity in the wide format data of a variable.

entidx2

index of an entity in the wide format data of a variable.

entidx3

index of an entity in the wide format data of a variable.

entidx4

index of an entity in the wide format data of a variable.

entidx5

index of an entity in the wide format data of a variable.

entidx6

index of an entity in the wide format data of a variable.

Examples

## Phase Portrait with Modeles Trajectories over 30 years with the following two models:
## dx  = + 0.0012 /x^2 and dy = + 0.0071 x^3

phaseportmod(datap, 30, datap$logGDP, datap$EmanzV, seq(0, 1, by = 0.1), seq(0, 1, by = 0.1),
param <- c(0.0012, 0.0071), f <- function(t,Y=c()) rbind(0.0012/Y[1]^2, + 0.0071*Y[1]^3), 
1, 2, 4, 5, 7, 9)